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基于判別鄰域嵌入算法的說話人識別

梁春燕,  袁文浩,  李艷玲,  夏斌,  孫文珠

梁春燕, 袁文浩, 李艷玲, 夏斌, 孫文珠. 基于判別鄰域嵌入算法的說話人識別[J]. 電子與信息學報, 2019, 41(7): 1774-1778. doi: 10.11999/JEIT180761
引用本文: 梁春燕, 袁文浩, 李艷玲, 夏斌, 孫文珠. 基于判別鄰域嵌入算法的說話人識別[J]. 電子與信息學報, 2019, 41(7): 1774-1778. doi: 10.11999/JEIT180761
Chunyan LIANG, Wenhao YUAN, Yanling LI, Bin XIA, Wenzhu SUN. Speaker Recognition Using Discriminant Neighborhood Embedding[J]. Journal of Electronics & Information Technology, 2019, 41(7): 1774-1778. doi: 10.11999/JEIT180761
Citation: Chunyan LIANG, Wenhao YUAN, Yanling LI, Bin XIA, Wenzhu SUN. Speaker Recognition Using Discriminant Neighborhood Embedding[J]. Journal of Electronics & Information Technology, 2019, 41(7): 1774-1778. doi: 10.11999/JEIT180761

基于判別鄰域嵌入算法的說話人識別

doi: 10.11999/JEIT180761
  • 1.

    山東理工大學計算機科學與技術學院 ??淄博 ??255049

  • 2.

    內(nèi)蒙古師范大學計算機與信息工程學院 ??呼和浩特 ??010022

基金項目: 國家自然科學基金(11704229, 61701286, 61562068)，山東省自然科學基金(ZR2017LA011, ZR2015FL003, ZR2017MF047)，山東省高等學?？萍加媱濏椖?J17KA078)，內(nèi)蒙古自然科學基金項目(2015MS0629)
詳細信息
    作者簡介:

    梁春燕：女，1986年生，講師，研究方向為說話人識別、語種識別

    袁文浩：男，1985年生，講師，研究方向為語音信號處理、語音增強

    李艷玲：女，1978年生，副教授，研究方向為自然語言處理、口語理解、機器學習

    夏斌：男，1973年生，副教授，研究方向為深度學習、信號與信息處理

    孫文珠：男，1983年生，講師，研究方向為多媒體信號傳輸

    通訊作者:

    梁春燕　liangchunyan@sdut.edu.cn

  • 中圖分類號: TP391.42

Speaker Recognition Using Discriminant Neighborhood Embedding

  • 1.

    College of Computer Science and Technology, Shandong University of Technology, Zibo 255049, China

  • 2.

    College of Computer and Information Engineering, Inner Mongolia Normal University, Hohhot 010022, China

Funds: The National Natural Science Foundation of China (11704229, 61701286, 61562068), The Shandong Provincial Natural Science Foundation (ZR2017LA011, ZR2015FL003, ZR2017MF047), The Project of Shandong Province Higher Educational Science and Technology Program (J17KA078), The Natural Science Foundation of Inner Mongolia Autonomous Region of China (2015MS0629)
  • 摘要: 該文提出一種基于判別鄰域嵌入(DNE)算法的說話人識別。判別鄰域嵌入算法作為流形學習方法的一種，可以通過構建鄰接圖獲取數(shù)據(jù)的局部鄰域結構信息；同時該算法可以充分利用類間判別信息，具有更強的判別能力。在美國國家標準技術研究院2010年說話人識別評測(NIST SRE 2010)電話-電話核心測試集上的實驗結果表明了該算法的有效性。
    Abstract: Discriminant Neighborhood Embedding (DNE) algorithm is introduced into the speaker recognition system. DNE is a manifold learning approach and aims at preserving the local neighborhood structure on the data manifold. As well, DNE has much more power in discrimination by sufficiently using the between-class discriminant information. The experimental results on the telephone-telephone core condition of the NIST 2010 Speaker Recognition Evaluation (SRE) dataset indicate the effectiveness of DNE algorithm.
    • HTML全文

  • 表  1  NIST SRE 2010電話-電話測試集上DNE和NPE的EER和minDCF比較(無信道補償)

    系統(tǒng)男聲 女聲
    EER(%)minDCFEER(%)minDCF
    NPE5.760.0575 6.980.0744
    DNE5.280.05446.350.0683
    下載: 導出CSV

    表  2  NIST SRE 2010電話-電話測試集上DNE和NPE的EER和minDCF比較(LDA信道補償)

    系統(tǒng)男聲 女聲
    EER(%)minDCFEER(%)minDCF
    NPE+LDA4.710.0492 6.110.0633
    DNE+LDA4.190.04535.570.0604
    下載: 導出CSV

    表  3  NIST SRE 2010電話-電話測試集上DNE和NPE的EER和minDCF比較(WCCN信道補償)

    系統(tǒng)男聲 女聲
    EER(%)minDCFEER(%)minDCF
    NPE+WCCN5.070.0512 6.490.0677
    DNE+WCCN4.590.04785.830.0617
    下載: 導出CSV

    表  4  NIST SRE 2010電話-電話測試集上DNE和NPE的EER和minDCF比較(LDA+WCCN信道補償)

    系統(tǒng)男聲 女聲
    EER(%)minDCFEER(%)minDCF
    NPE+LDA+WCCN4.410.0476 5.720.0584
    DNE+LDA+WCCN4.150.04345.240.0553
    下載: 導出CSV

    表  5  NIST SRE 2010電話-電話測試集上DNE和PLDA的EER和minDCF比較

    系統(tǒng)男聲 女聲
    EER(%)minDCFEER(%)minDCF
    DNE+LDA+WCCN4.150.0434 5.240.0553
    PLDA4.120.04285.370.0532
    下載: 導出CSV
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出版歷程
  • 收稿日期:  2018-08-03
  • 修回日期:  2019-01-21
  • 網(wǎng)絡出版日期:  2019-02-24
  • 刊出日期:  2019-07-01

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